Remote Senior Machine Learning Engineer

3 billion people across the world work in frontline jobs. Yet, despite rising costs and staff shortages, frontline organisations are still left to choose between paper, Excel, and WhatsApp, or decade-old workforce management solutions to take care of the most important part of their businesses - their people. Enter Sona: the next generation of AI-native, frontline workforce management. We've built an end-to-end platform covering Scheduling, HR, Payroll, and Communications that gives the largest frontline organisations everything they need to staff more intelligently and empower their teams.

In under 5 years, we've already made a deep impact on the lives of over 100k frontline workers and the operation of their organisations, grown the team to 140+, and secured over $100M in funding from notable VCs. It's a hugely exciting time to be joining the team as we're still small enough that you'll have a significant impact on the company's growth trajectory and culture, yet large enough to have a great structure, experienced leaders and world-class benefits in place.

About the Role

You'll join a two-person ML team that has built a production forecasting system running daily half-hourly predictions across multiple restaurant chains. Our forecasting models enter into a complex environment with key machine and human decisions being made on their predictions, facing feedback loops and a highly variable environment. The system works - the challenge now is scaling it from a handful of clients to 100s. You'll own client launches end-to-end: validating data, selecting models, running UAT, going live, and monitoring performance afterwards. You'll join client calls, build relationships, and understand what actually matters on the ground - not just whether the model is accurate, but whether the kitchen prepped the right amount of food.

You'll love this role if:

• You enjoy taking ownership of the product and outcome end-to-end.
• Machine learning at Sona is a success if we have happy clients running successful businesses as well as the models which are best in industry.
• You have a focus on solving the problem and when given the choice between 'complicated and shiny' vs 'get something simple in front of a user', you choose the latter.
• You're excited by working with our industry experts to really understand what's happening in our client's businesses and the realities of working there.
• You see beyond the data to the world that resulted in this data generating process, the issues that come with it and the opportunity that it gives us.
• You're experienced in and excited by taking a machine learning project from business idea to deployed production system.
• You default to AI tools for development. You use Claude Code, Cursor, or equivalent daily - not as a novelty, but as your standard working mode.

Our role won't be for you if:

• You're hoping to do research and publish research papers as a key element of the work that you do.
• You're looking to move into a less technical, more managerial role.
• You're keen to get your hands on fancy new technology X and apply it to something.
• You prefer to work on one thing and make it perfect before moving on - the role requires pragmatism, parallelism, and iterative improvement.

Requirements

You'll need these skills/experience to be successful:

• Production ML experience, with a track record of deploying ML systems that handle messy data, fail gracefully, and need monitoring.
• Strong ML fundamentals - you can reason about trade-offs in practice, explain why certain features matter more than model selection, and make good judgement calls when something unexpected happens.
• Client-facing deployment experience - you've personally owned an ML deployment end-to-end and are comfortable on calls with non-technical stakeholders.
• Strong programming skills in Python, including the ML/scientific Python stack (e.g. numpy, scikit-learn).
• Daily use of AI development tools (Claude Code, Cursor, Copilot or equivalent) as your default working mode.

It would be great if you have experience in some of these areas too:

• Forecasting, time-series, or demand-planning - someone who understands lag features, calendar effects, and evaluation integrity intuitively will ramp significantly faster.

Our stack: Python, scikit-learn, MLflow, Docker, GCP. A small team where ownership is wide and context-switching is normal.

Benefits

• Salary: £95,000-£110,000
• Fully remote (European timezones)
• Share options
• 35 days annual leave (25 days standard plus 10 flexible public holiday days)
• Extra day of leave for every year of service
• Pension contributions matched up to 5%
• Comprehensive health insurance
• Enhanced parental leave